Difference Between Fixed Point And Equilibrium Point

Fixed points and equilibrium points are fundamental concepts in mathematics and have broad applications across various fields such as economics, physics, and biology. Both terms refer to specific values or states in a system where certain conditions hold true, but they are not interchangeable. Understanding the distinctions between these points can clarify their roles and significance in different contexts.

A fixed point refers to a value that remains constant under a given function or transformation. In contrast, an equilibrium point is a state where a system remains stable under external forces or changes, often represented in differential equations. Recognizing the difference between these concepts is crucial for accurately applying them in theoretical and practical scenarios.

These points are vital in analyzing and predicting the behavior of complex systems. Fixed points help identify invariant states in iterative processes, while equilibrium points aid in understanding stability and dynamics in physical and biological systems. Grasping these concepts enhances our ability to model and solve real-world problems effectively.

Basic Concepts

Definition of Fixed Point

Mathematical Definition

A fixed point is a value that remains unchanged when a specific function is applied to it. Formally, if 𝑓(π‘₯)f(x) is a function, a point π‘₯x is a fixed point if 𝑓(π‘₯)=π‘₯f(x)=x. This means that applying the function to π‘₯x returns π‘₯x itself.

Common Examples

  • Identity Function: For the function 𝑓(π‘₯)=π‘₯f(x)=x, every point is a fixed point because 𝑓(π‘₯)=π‘₯f(x)=x.
  • Quadratic Function: Consider 𝑓(π‘₯)=π‘₯2f(x)=x2. Here, the points π‘₯=0x=0 and π‘₯=1x=1 are fixed points because 02=002=0 and 12=112=1.
  • Logistic Map: For the function 𝑓(π‘₯)=π‘Ÿπ‘₯(1βˆ’π‘₯)f(x)=rx(1βˆ’x), where π‘Ÿr is a parameter, the fixed points can be found by solving the equation π‘Ÿπ‘₯(1βˆ’π‘₯)=π‘₯rx(1βˆ’x)=x.

Definition of Equilibrium Point

Mathematical Definition

An equilibrium point is a state of a system where all forces or changes balance out, resulting in no net change. In a differential equation, an equilibrium point occurs where the derivative is zero, indicating that the system is stable at that point.

Common Examples

  • Physical Systems: In a pendulum, the equilibrium points are where the pendulum is at rest (either hanging straight down or inverted at the top).
  • Chemical Reactions: In chemical equilibrium, the rates of the forward and reverse reactions are equal, resulting in no net change in the concentrations of reactants and products.
  • Biological Systems: In population dynamics, an equilibrium point can be a stable population size where birth and death rates balance.
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Conceptual Differences

Fixed Points in Different Contexts

Fixed points are primarily used in mathematics and computer science. They help identify invariant states in iterative processes and functions. For example, in numerical methods, fixed points are used to find roots of equations or to analyze the stability of algorithms.

Equilibrium Points in Different Contexts

Equilibrium points are used in physics, biology, and economics to understand stable states of systems. They represent conditions where a system experiences no net change, which is crucial for analyzing dynamic behavior and predicting future states.

Mathematical Formulation

Equations and Functions

  • Fixed Points: For a function 𝑓(π‘₯)f(x), solve 𝑓(π‘₯)=π‘₯f(x)=x to find fixed points.
  • Equilibrium Points: For a differential equation 𝑑𝑦𝑑𝑑=𝑓(𝑦)dtdy​=f(y), find points where 𝑓(𝑦)=0f(y)=0 to identify equilibrium points.

Stability and Conditions

  • Fixed Points Stability: A fixed point π‘₯x is stable if small perturbations around π‘₯x do not diverge. This can be analyzed using the derivative of 𝑓(π‘₯)f(x). If βˆ£π‘“β€²(π‘₯)∣<1∣fβ€²(x)∣<1, the fixed point is stable.
  • Equilibrium Points Stability: An equilibrium point is stable if small perturbations return to the equilibrium. This is analyzed using the Jacobian matrix in multi-dimensional systems. If the real parts of all eigenvalues of the Jacobian are negative, the equilibrium is stable.


Fixed Points in Real Life


In economics, fixed points help identify steady states in models. For example, in market equilibrium, the fixed point represents a price where supply equals demand, and there is no incentive for buyers or sellers to change their behavior.

Game Theory

In game theory, Nash equilibrium is a fixed point where no player can improve their payoff by unilaterally changing their strategy. This concept is essential for predicting outcomes in competitive situations.

Equilibrium Points in Real Life


In physics, equilibrium points are used to analyze stable configurations of systems. For example, in mechanics, equilibrium points help determine the positions where forces balance, such as the resting position of a spring.


In biology, equilibrium points are crucial for understanding population dynamics. They indicate stable population sizes where birth and death rates balance, helping predict long-term population trends.

Detailed Examples

Fixed Point Examples

Graphical Illustrations

Consider the function 𝑓(π‘₯)=cos⁑(π‘₯)f(x)=cos(x). To find the fixed points, solve cos⁑(π‘₯)=π‘₯cos(x)=x. Graphically, this can be illustrated by plotting 𝑦=cos⁑(π‘₯)y=cos(x) and 𝑦=π‘₯y=x on the same axes. The points where the two curves intersect are the fixed points.

Step-by-Step Solutions

  1. Define the function: 𝑓(π‘₯)=cos⁑(π‘₯)f(x)=cos(x).
  2. Set up the equation: cos⁑(π‘₯)=π‘₯cos(x)=x.
  3. Graph the function: Plot 𝑦=cos⁑(π‘₯)y=cos(x) and 𝑦=π‘₯y=x.
  4. Identify intersections: The points where the curves intersect are the fixed points.
  5. Verify solutions: Check the solutions by substituting back into the equation.

Equilibrium Point Examples

Graphical Illustrations

Consider the differential equation 𝑑𝑦𝑑𝑑=𝑦(1βˆ’π‘¦)dtdy​=y(1βˆ’y). To find the equilibrium points, solve 𝑦(1βˆ’π‘¦)=0y(1βˆ’y)=0. Graphically, this can be illustrated by plotting 𝑦(1βˆ’π‘¦)y(1βˆ’y) and identifying the points where the curve intersects the x-axis.

Step-by-Step Solutions

  1. Define the differential equation: 𝑑𝑦𝑑𝑑=𝑦(1βˆ’π‘¦)dtdy​=y(1βˆ’y).
  2. Set up the equation: 𝑦(1βˆ’π‘¦)=0y(1βˆ’y)=0.
  3. Solve for 𝑦y: Find the values of 𝑦y that satisfy the equation.
  4. Graph the function: Plot 𝑦(1βˆ’π‘¦)y(1βˆ’y) and identify intersections with the x-axis.
  5. Verify solutions: Check the stability of each equilibrium point by analyzing the sign of the derivative around the points.
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Calculating Methods

Fixed Points Calculation

Iterative Methods

Iterative methods are a common approach to finding fixed points. These methods repeatedly apply a function to an initial guess until the result converges to a fixed point.

  • Fixed Point Iteration: Start with an initial guess π‘₯0x0​. Compute π‘₯𝑛+1=𝑓(π‘₯𝑛)xn+1​=f(xn​) and repeat until π‘₯𝑛xn​ stabilizes.
  • Newton’s Method: This method is used when the function is differentiable. Start with an initial guess π‘₯0x0​. Compute π‘₯𝑛+1=π‘₯π‘›βˆ’π‘“(π‘₯𝑛)𝑓′(π‘₯𝑛)xn+1​=xnβ€‹βˆ’fβ€²(xn​)f(xn​)​. Repeat until the values converge.

Example of Fixed Point Iteration:

  1. Choose an initial guess: Let π‘₯0=1x0​=1.
  2. Apply the function: If 𝑓(π‘₯)=cos⁑(π‘₯)f(x)=cos(x), compute π‘₯1=cos⁑(π‘₯0)x1​=cos(x0​).
  3. Iterate: Repeat the process until π‘₯π‘›β‰ˆπ‘₯𝑛+1xnβ€‹β‰ˆxn+1​.

Analytical Methods

Analytical methods involve solving the equation 𝑓(π‘₯)=π‘₯f(x)=x directly. These methods are exact but may not always be possible, especially for complex functions.

  • Algebraic Solutions: Solve the equation 𝑓(π‘₯)=π‘₯f(x)=x using algebraic manipulation.
  • Graphical Solutions: Plot 𝑦=𝑓(π‘₯)y=f(x) and 𝑦=π‘₯y=x. The points where the curves intersect are the fixed points.

Example of Analytical Solution:

  1. Define the function: 𝑓(π‘₯)=π‘₯2βˆ’π‘₯+1f(x)=x2βˆ’x+1.
  2. Set up the equation: Solve π‘₯2βˆ’π‘₯+1=π‘₯x2βˆ’x+1=x.
  3. Solve for π‘₯x: Simplify to π‘₯2βˆ’2π‘₯+1=0x2βˆ’2x+1=0, then solve π‘₯=1x=1.

Equilibrium Points Calculation

Stability Analysis

Stability analysis determines whether an equilibrium point is stable or unstable. This involves examining the behavior of the system near the equilibrium point.

  • Linear Stability Analysis: Linearize the system around the equilibrium point and analyze the eigenvalues of the Jacobian matrix.
  • Lyapunov Methods: Use Lyapunov functions to determine stability without linearizing the system.

Example of Linear Stability Analysis:

  1. Identify the equilibrium point: For 𝑑𝑦𝑑𝑑=𝑦(1βˆ’π‘¦)dtdy​=y(1βˆ’y), equilibrium points are 𝑦=0y=0 and 𝑦=1y=1.
  2. Linearize the system: Compute the Jacobian matrix at each equilibrium point.
  3. Analyze eigenvalues: Determine the stability based on the signs of the eigenvalues.

Linear and Non-linear Systems

  • Linear Systems: Stability can be easily determined using eigenvalues of the system matrix.
  • Non-linear Systems: More complex methods, like Lyapunov functions or numerical simulations, are often required.

Stability and Convergence

Stability Analysis

Fixed Points Stability:

  • Local Stability: A fixed point π‘₯βˆ—xβˆ— is locally stable if βˆ£π‘“β€²(π‘₯βˆ—)∣<1∣fβ€²(xβˆ—)∣<1.
  • Global Stability: A fixed point is globally stable if all points in the domain converge to π‘₯βˆ—xβˆ— under iteration.

Equilibrium Points Stability:

  • Asymptotic Stability: An equilibrium point is asymptotically stable if perturbations decay over time.
  • Marginal Stability: An equilibrium point is marginally stable if perturbations neither grow nor decay.

Convergence Criteria

Convergence in Fixed Points:

  • Convergence Rate: The rate at which an iterative method approaches a fixed point. Newton’s method has a quadratic convergence rate.
  • Convergence Conditions: For π‘₯𝑛+1=𝑓(π‘₯𝑛)xn+1​=f(xn​), if βˆ£π‘“β€²(π‘₯βˆ—)∣<1∣fβ€²(xβˆ—)∣<1, the method converges.
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Convergence in Equilibrium Points:

  • Lyapunov’s Direct Method: Construct a Lyapunov function 𝑉(π‘₯)V(x) such that 𝑉(π‘₯)>0V(x)>0 and 𝑉˙(π‘₯)<0VΛ™(x)<0.
  • Numerical Simulations: Use simulations to observe convergence behavior in non-linear systems.

Advanced Topics

Fixed Points in Dynamical Systems

Chaotic Behavior:

  • Definition: Chaos refers to sensitive dependence on initial conditions, leading to unpredictable behavior.
  • Example: The logistic map 𝑓(π‘₯)=π‘Ÿπ‘₯(1βˆ’π‘₯)f(x)=rx(1βˆ’x) exhibits chaotic behavior for certain values of π‘Ÿr.


  • Definition: Bifurcations occur when a small change in a parameter causes a qualitative change in system behavior.
  • Example: In the logistic map, varying π‘Ÿr leads to period-doubling bifurcations and chaos.

Equilibrium Points in Complex Systems

Multistable Systems:

  • Definition: Systems with multiple stable equilibrium points.
  • Example: A double-well potential has two stable points and one unstable point.

Oscillatory Systems:

  • Definition: Systems that exhibit oscillations around equilibrium points.
  • Example: Predator-prey models exhibit oscillatory behavior due to the interaction between species.

Practical Considerations

Choosing Between Fixed and Equilibrium Points

Context-Based Selection:

  • Mathematical Models: Use fixed points in iterative processes and functions.
  • Dynamic Systems: Use equilibrium points in systems described by differential equations.

Advantages and Limitations:

  • Fixed Points: Easier to calculate and analyze in simple functions. May not exist for all functions.
  • Equilibrium Points: Provide insights into system stability. Complex to analyze in non-linear systems.

Common Pitfalls

Misinterpretation of Results:

  • Fixed Points: Confusing fixed points with periodic points can lead to incorrect conclusions.
  • Equilibrium Points: Misinterpreting stability analysis can result in incorrect predictions about system behavior.

Incorrect Application of Concepts:

  • Context Misapplication: Applying fixed point analysis to dynamic systems or vice versa can lead to errors.
  • Overlooking Conditions: Ignoring the conditions required for stability or convergence can lead to incorrect results.

Frequently Asked Questions

What is a fixed point in mathematics?

A fixed point in mathematics is a value that remains unchanged under a specific function or transformation. For example, if 𝑓(π‘₯)=π‘₯f(x)=x, then π‘₯x is a fixed point. This concept is widely used in iterative methods and computational algorithms to find stable solutions.

What is an equilibrium point?

An equilibrium point is a state of a system where all forces or changes balance out, resulting in no net change. In differential equations, it represents a point where the derivative is zero, indicating stability. Equilibrium points are crucial in studying the dynamics of physical, chemical, and biological systems.

How do fixed points and equilibrium points differ?

Fixed points refer to values that remain constant under a function, while equilibrium points are states of stability in a system. The primary difference lies in their application: fixed points are used in mathematical functions and iterative processes, whereas equilibrium points are used in dynamic systems to analyze stability.

Why are fixed points important in economics?

Fixed points in economics help identify steady states in models, such as market equilibrium or optimal strategies in game theory. These points are essential for predicting long-term outcomes and understanding the behavior of economic agents under various conditions.

Can a system have multiple equilibrium points?

Yes, a system can have multiple equilibrium points, each representing different stable states. In complex systems, these points can indicate various scenarios or conditions under which the system can remain stable, such as different levels of population in ecological models or multiple market equilibria in economics.


Understanding the difference between fixed points and equilibrium points is essential for accurately applying these concepts in various fields. While fixed points provide insights into invariant states in mathematical functions, equilibrium points offer a deeper understanding of stability in dynamic systems.

By grasping these concepts, we can better analyze, model, and predict the behavior of complex systems. This knowledge not only enhances theoretical understanding but also aids in solving practical problems in diverse domains, from economics to biology.

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